Stochastic bounds and histograms for active queues management and networks analysis

  • Farah Aït-Salaht
  • , Hind Castel-Taleb
  • , Jean Michel Fourneau
  • , Nihal Pekergin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present an extension of a methodology based on monotonicity of various networking elements and measurements performed on real networks. Assuming the stationarity of flows, we obtain histograms (distributions) for the arrivals. Unfortunately, these distributions have a large number of values and the numerical analysis is extremely time-consuming. Using the stochastic bounds and the monotonicity of the networking elements, we show how we can obtain, in a very efficient manner, guarantees on performance measures. Here, we present two extensions: the merge element which combine several flows into one, and some Active Queue Management (AQM) mechanisms. This extension allows to study networks with a feed-forward topology.

Original languageEnglish
Title of host publicationAnalytical and Stochastic Modelling Techniques and Applications - 23rd International Conference, ASMTA 2016, Proceedings
EditorsTuan Phung-Duc, Sabine Wittevrongel
PublisherSpringer Verlag
Pages1-16
Number of pages16
ISBN (Print)9783319439037
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event23rd International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2016 - Cardiff, United Kingdom
Duration: 24 Aug 201626 Aug 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9845 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2016
Country/TerritoryUnited Kingdom
CityCardiff
Period24/08/1626/08/16

Keywords

  • Histograms
  • Performance evaluation
  • Queue management
  • Stochastic bounds

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